1. Field of Invention
The present invention pertains to the field of designing graph structures. More particularly, this invention relates to deriving a genome representation for evolving the weights in a graph structure.
2. Art Background
A variety of disciplines including computer science commonly express solutions to problems in the form of graph structures. For example, neural networks which are commonly used in computer-related applications may be expressed in the form of graph structures.
A graph structure typically includes a set of nodes and a set of arcs that provide interconnections among the nodes. Each arc of a graph structure usually has an associated weight. The design of a graph structure typically involves determining an appropriate arrangement of nodes and arcs and determining an appropriate weight for each arc.
One prior method for determining the weights in a graph structure is to use genetic programming techniques to evolve the weights. A typical genetic programming method involves generating an initial population of organisms each of which is a candidate solution for the weights, selecting a subset of organisms from the initial population for use as parents of a generation of child organisms, and generating the child organisms by combining genetic material from the parent organisms using genetic operators such as mutation and cross-over. Typically, many generations of child organisms are generated and tested before a suitable set of weights is found.
The genetic operators of mutation and crossover are usually applied to an arrangement of genetic material which is commonly referred to as a genome representation for the weights. It is usually desirable to employ a genome representation that will yield the most efficient evolution to a desired solution. For example, a reduction in the number of generations of organisms that are generated and evaluated usually decreases the time it takes to reach a desired solution and decreases the overall design cost of a graph structure.